Pipeline Coverage Models

Pipeline coverage is something every sales manager talks about, but few really understand it, that is, most of the time I see it mis-applied, so that it is meaningless, or even dangerously misleading.

Pipeline coverage refers to the number of qualified opportunities one must have in their qualified pipelines to make their number. Calculating pipeline coverage is easy, we can all do it in our sleep. We simply divide the number and value of the deals we need to make our number, by our win rate. The two numbers that result are the total number of deals and the value of the deals we must maintain in our qualified pipeline.

If we have a “3X” pipeline coverage model, implicitly we are saying we have a 33% win rate. Stated differently, for every 3 qualified deals we have in our pipeline, we expect to win 1.

All simple, all sales management 101.

Now here’s where things start going tragically wrong:

We apply that number to everyone in the organization. A high performing sales person may have a win rate of 50%, needing only “2X” coverage. Not only do we piss that sales person off by requiring them to have more, but we threaten their performance by diverting them from the deals they would focus on to finding more deals just to make the general coverage model. So we actually may lower their performance and win rates by forcing them into a global coverage model.

Likewise, a poor performer may have a win rate of 20%. This would require a coverage model of 5X. But since we’ve set the coverage at 3X, we are establishing a goal that will cause them to fall short of their numbers. “But I did what you told me to do boss……”

We have to establish healthy pipeline metrics for each person on the team, coaching them on how to improve.

Pipeline coverage is meaningless without pipeline integrity. If your pipeline is filled with garbage, you will achieve your coverage model, but here’s the death spiral. Your win rates go down, because you have bad quality deals, so now your 3X coverage is unsatisfactory. You need to change something to make your number. Unfortunately, too many managers are either oblivious to what this means or too lazy to dive into the issues.

I actually met with a VP of Sales who said, “We need to move our coverage to 6-7 times (7 times implies a win rate of 14%). Clearly, he knew how to do the pipeline math, but he wasn’t taking the time to understand what was driving the numbers. He wasn’t looking at, “Do we have real qualified opportunities in our pipeline, or do we have crap?” “Why is our win rate declining, what do we need to do about it?” The purpose of this is not a math exercise. The purpose is to understand the dynamics of your pipeline, then start engineering things to tilt the numbers in your favor (more on this later). First, they need to inspect the pipeline maintaining rigorous quality. Are these real deals? Are they qualified? Why is our win rate declining, what do we need to do to improve it (or it may be our average transaction size or our sales cycle).

The pipeline coverage metric is probably the most easily gamed metric in sales. Sales people can always meet their coverage number, simply by lowering the quality of the deals they stuff into the pipeline. It’s not their fault–they are doing what management is telling them to do. It’s management’s responsibility to make sure sales people understand what a quality deal looks like and to make sure the pipelines are filled with quality deals.

Pipeline coverage is meaningless without velocity. Let’s say we have a high quality pipeline, it’s hitting our coverage goal, but a large number of deals are stalled. We won’t hit our number. Pipeline coverage, velocity (based on average sales cycle) go han in hand. We have to have both, in balance, or pipeline coverage is useless.

Our pipeline number ripple through to our healthy prospecting numbers. For example, if 1 in 10 prospects results in a qualified opportunity, we now have guidance about the prospecting we need to do to maintain healthy pipelines.

If we have bad logic or bad numbers for our pipelines, it will drive the wrong assessment of what we need to do in prospecting.

We need to constantly reassess these metrics to tilt them in our favor. We aren’t “prisoners” of the math (as the VP of Sales cited above was), we engineer these numbers, tilting them in our favor. Have we defined the ICP and are we focusing on this? How do we improve deal quality? What can we do to improve win rates, average transaction value, sales cycle?

Too many managers and sales people don’t understand their pipeline metrics, consequently, are challenged in meeting goals regardless of what measure has been established.

Too many managers and sales people focus on the math–the calculation, without understanding we control or at least influence the formulas. Math always works, a 33% win rate will always create the need for 3X coverage. But things change, if we start looking at, “What if our win rate is 50%, how do we make that happen?” Ironically, if we answer that question, we work on far fewer deals, we have to prospect far fewer. Alternatively, we can leverage this to drive higher revenue growth.

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In addition to what you point out in your initial posting, there’s also the mix to consider.

Win rate is about the number of deals you win as a percentage of those you qualify in overall.

But what about VALUE? You might have a win rate of 50% for small deals, and 20% for large deals.

And how are these distributed in your funnel?

Have you $1M in your funnel, spread across 50 smaller deals, or is it tied up in 5 big deals? What is your vulnerability with each? And why is it your better with the small deals vs the big deals? Do you qualify differently, are you less confident in handling the bigger stuff?

Sales people and managers love simplicity – we all do deep down. I wonder if, in their quest and race to close deals and take home a big fat commission check, they are unable (or unwilling!) to see that perhaps they are taking an overly simplistic approach?

There’s a reason why sales people are overall getting worse and worse at closing, as evidenced over the last 5-7 years of data you recently referenced David. Could this be partly driving that trend?

Actually, these are so powerful, we want to look at balance–perhaps across product lines, industry segments, new logos/current customers, distribution of average deal size, time in stage and many other things.

We are becoming increasingly data driven, we have more data at our fingertips than ever before. The problem is we don’t take the time to understand what the data means.

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This is Dave Brock's Blog. It offers my views on a variety of business, sales, marketing, and leadership topic. My goal is to make a difference for you, the reader, in both your professional and personal lives.

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